Search engines may output lists of hyperlinks for web pages that include information of interest. Some search engines base the determination of corresponding hyperlinks on a search query entered by the user. The goal of the search engine is to return links for high quality, relevant sites based on the search query. Most commonly, search engines accomplish this by matching the terms in the search query to a database of stored web pages or web page content. Web pages that include the terms in the search query are considered “hits” and are included in the list of hyperlinks presented to the user.
To increase efficacy of the search, a search engine may rank the list of hits or hyperlinks according to the relevance or quality. For example, the search engine may assign a grade or rank to each hit, and the score may be assigned to correspond to the relevance or importance of the web page. Conventional methods of determining importance or relevance are based on the content of each web page including the link structure of the web page.
Many conventional search engines utilize an indexing system for identifying web pages available on the Internet. The indexing system identifies words in the pages and creates an index of those words. The system responds to user queries by analyzing the index and identifying the pages that are most relevant to the users query.
The relevance ranking or determination can be executed in various ways. The citation of one site or page by other sites or pages is sometimes used as one measure of relevance. Web page metadata is also sometimes used in a determination of relevance.
Neural networks have also been used in the field of Internet searching. It is assumed, for purposes of this description, that the reader is familiar with how neural networks operate. A neural network can consist of three basic aspects—a neuron or node, definitions of how the neurons or nodes are interconnected or related to each other, and the manner in which that topology is updated over time.